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- W2002053017 abstract "The use of technology in every day tasks enables the possibility to collect large amounts of observations of events taking place in different environments. Most tools are capable of storing a detailed account of the operations executed by users in certain files commonly known as logs. These files can be further analyzed to infer information that is not directly visible such as the most popular applications, times of the day with highest activity, calories burnt after a running session, etc. Graphic visualizations of this data can be used to support this type of analysis as shown in [1]. Visualization can also be applied in the domain of learning experiences to track and analyse the data obtained from both learners and instructors. There are several tools that have been proposed in specific environments such as, for example, in personal learning environments [5], to foster self-reflection and awareness [2], and to support instructors in web-based distance learning [3]. These visualizations need to take into account aspects such as how to access and protect personal data, filter management, multi-user support and availability. In this paper, the web-based visualization platform GLASS (Gradient's Learning Analytics System) is presented. The architecture of the tool has been conceived to support a large number of modular visualizations derived from a common dataset containing a large number of recorded events. The tool was developed following a bottom-up methodology to provide a set of basic operations required by any visualization. The design goal is to provide a highly versatile, modular platform that simplifies the implementation of new visualizations." @default.
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- W2002053017 date "2012-04-29" @default.
- W2002053017 modified "2023-09-26" @default.
- W2002053017 title "GLASS" @default.
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- W2002053017 doi "https://doi.org/10.1145/2330601.2330642" @default.
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